### Total number of active reporters during Phase 2 ####
###Active Reporters, cluster-robust SE
mod.pooled.clst <- lm_robust(active.ever ~ Responsiveness + recruitment + lc1.announce + Recruited.Phase2, data=ph2.reporters,
                             clusters = location.id)
mod.pooled.ci <- cbind(mod.pooled.clst$conf.low, mod.pooled.clst$conf.high)

mod.one.clst <- lm_robust(active.ever ~ Responsiveness + recruitment, data=ph2.reporters[ph2.reporters$Recruited.Phase2==0,],
                          clusters = location.id)
mod.one.ci <- cbind(mod.one.clst$conf.low, mod.one.clst$conf.high)

mod.two.clst <- lm_robust(active.ever ~ Responsiveness + recruitment + lc1.announce, data=ph2.reporters[ph2.reporters$Recruited.Phase2==1,],
                          clusters = location.id)
mod.two.ci <- cbind(mod.two.clst$conf.low, mod.two.clst$conf.high)


###Active Reporters, naive for model objects
mod.pooled <- lm(active.ever ~ Responsiveness + recruitment + lc1.announce + Recruited.Phase2, data=ph2.reporters)

mod.one <- lm(active.ever ~ Responsiveness + recruitment, data=ph2.reporters[ph2.reporters$Recruited.Phase2==0,])

mod.two <- lm(active.ever ~ Responsiveness + recruitment + lc1.announce, data=ph2.reporters[ph2.reporters$Recruited.Phase2==1,])

#Table
stargazer(mod.pooled, mod.one, mod.two, type = "latex", 
          dep.var.caption  = "DV: At Least One Report During Phase 2",
          dep.var.labels.include = FALSE,
          covariate.labels = c("Responsiveness","Neighbor Nomination","LC1 Nomination","LC1 Announcement","Phase 2","Intercept"),
          ci = TRUE,
          ci.custom = list(mod.pooled.ci,
                           mod.one.ci,
                           mod.two.ci),
          df = FALSE, omit.stat = c("rsq","ser","f"),
          intercept.bottom = TRUE,
          notes = "", notes.append = FALSE, notes.label = "",
          column.labels = c("(Pooled)","(P1 Recruits)","(P2 Recruits)"),
          report = c('vcs'), model.numbers = FALSE
)

### Total number of reports submitted by each reporter during Phase 2 ####
###Total responses, cluster-robust SE
mod.pooled.clst <- lm_robust(total.responses ~ Responsiveness + recruitment + lc1.announce + Recruited.Phase2, data=ph2.reporters,
                             clusters = location.id)
mod.pooled.ci <- cbind(mod.pooled.clst$conf.low, mod.pooled.clst$conf.high)

mod.one.clst <- lm_robust(total.responses ~ Responsiveness + recruitment, data=ph2.reporters[ph2.reporters$Recruited.Phase2==0,],
                          clusters = location.id)
mod.one.ci <- cbind(mod.one.clst$conf.low, mod.one.clst$conf.high)

mod.two.clst <- lm_robust(total.responses ~ Responsiveness + recruitment + lc1.announce, data=ph2.reporters[ph2.reporters$Recruited.Phase2==1,],
                          clusters = location.id)
mod.two.ci <- cbind(mod.two.clst$conf.low, mod.two.clst$conf.high)

###Total responses, naive for model objects
mod.pooled <- lm(total.responses ~ Responsiveness + recruitment + lc1.announce + Recruited.Phase2, data=ph2.reporters)

mod.one <- lm(total.responses ~ Responsiveness + recruitment, data=ph2.reporters[ph2.reporters$Recruited.Phase2==0,])

mod.two <- lm(total.responses ~ Responsiveness + recruitment + lc1.announce, data=ph2.reporters[ph2.reporters$Recruited.Phase2==1,])

#Table
stargazer(mod.pooled, mod.one, mod.two, type = "latex", 
          dep.var.caption  = "DV: Total Number of Reports During Phase 2",
          dep.var.labels.include = FALSE,
          covariate.labels = c("Responsiveness","Neighbor Nomination","LC1 Nomination","LC1 Announcement","Phase 2","Intercept"),
          ci = TRUE,
          ci.custom = list(mod.pooled.ci,
                           mod.one.ci,
                           mod.two.ci),
          df = FALSE, omit.stat = c("rsq","ser","f"),
          intercept.bottom = TRUE,
          notes = "", notes.append = FALSE, notes.label = "",
          column.labels = c("(Pooled)","(P1 Reporters)","(P2 Reporters)"),
          report = c('vcs'), model.numbers = FALSE
)

### Number of reports submitted by each reporter during the last two weeks of Phase 2 ####
###Last two weeks, cluster-robust SE
mod.pooled.clst <- lm_robust(last2week.responses ~ Responsiveness + recruitment + lc1.announce + Recruited.Phase2, data=ph2.reporters,
                             clusters = location.id)
mod.pooled.ci <- cbind(mod.pooled.clst$conf.low, mod.pooled.clst$conf.high)

mod.one.clst <- lm_robust(last2week.responses ~ Responsiveness + recruitment, data=ph2.reporters[ph2.reporters$Recruited.Phase2==0,],
                          clusters = location.id)
mod.one.ci <- cbind(mod.one.clst$conf.low, mod.one.clst$conf.high)

mod.two.clst <- lm_robust(last2week.responses ~ Responsiveness + recruitment + lc1.announce, data=ph2.reporters[ph2.reporters$Recruited.Phase2==1,],
                          clusters = location.id)
mod.two.ci <- cbind(mod.two.clst$conf.low, mod.two.clst$conf.high)

###Last two weeks, naive for model objects
mod.pooled <- lm(last2week.responses ~ Responsiveness + recruitment + lc1.announce + Recruited.Phase2, data=ph2.reporters)

mod.one <- lm(last2week.responses ~ Responsiveness + recruitment, data=ph2.reporters[ph2.reporters$Recruited.Phase2==0,])

mod.two <- lm(last2week.responses ~ Responsiveness + recruitment + lc1.announce, data=ph2.reporters[ph2.reporters$Recruited.Phase2==1,])

#Table
stargazer(mod.pooled, mod.one, mod.two, type = "latex", 
          dep.var.caption  = "DV: Total Number of Reports During Last Two Weeks of Phase 2",
          dep.var.labels.include = FALSE,
          covariate.labels = c("Responsiveness","Neighbor Nomination","LC1 Nomination","LC1 Announcement","Phase 2","Intercept"),
          ci = TRUE,
          ci.custom = list(mod.pooled.ci,
                           mod.one.ci,
                           mod.two.ci),
          df = FALSE, omit.stat = c("rsq","ser","f"),
          intercept.bottom = TRUE,
          notes = "", notes.append = FALSE, notes.label = "",
          column.labels = c("(Pooled)","(P1 Reporters)","(P2 Reporters)"),
          report = c('vcs'), model.numbers = FALSE
)